PFI-RP: Advanced Anomaly Detection and Diagnostics for Electrical Devices and Networks

Information

  • NSF Award
  • 2414706
Owner
  • Award Id
    2414706
  • Award Effective Date
    9/1/2024 - 4 months ago
  • Award Expiration Date
    8/31/2027 - 2 years from now
  • Award Amount
    $ 1,000,000.00
  • Award Instrument
    Standard Grant

PFI-RP: Advanced Anomaly Detection and Diagnostics for Electrical Devices and Networks

The broader impact of this Partnerships for Innovation - Research Partnerships (PFI-RP) project is to enhance the reliability and security of electrical devices and networks within modern infrastructure including, but not limited to, buildings, manufacturing systems, and hospitals. This PFI-RP project introduces a smart sensor capable of detecting anomalies, pinpointing their locations, and diagnosing issues in electrical devices and networks. The algorithms and designs developed may also contribute to the broader field of anomaly detection and diagnosis beyond electrical signals. The project team will provide training to undergraduate and graduate students, in addition to middle school teachers. Collaborations with the Peach State Louis Stokes Alliances for Minority Participation (LSAMP) and the NSF Research Experiences for Undergraduates (REU) programs will be nurtured to support these efforts. Strategic partnerships with industry leaders offer vital insights and provide educational and leadership opportunities for graduate students and postdoctoral researchers.<br/><br/>The project brings together a strong partnership involving academia, represented by the University of Georgia (UGA), and prominent industry leaders, including General Electric (GE), United States Robins Air Force Base (RAFB), Siemens America (Siemens), and NEC Laboratories America (NEC) to explore the commercialization of an electrical sensing technology for scalable anomaly detection and diagnosis in electrical devices and networks. The UGA team has collaborated with industrial partners RAFB and GE successfully in anomaly detection and diagnosis in joint projects. The impact spans from small-scale applications (e.g., homes, buildings, factories) to large-scale scenarios (e.g., distribution networks to transmission networks of main grids). This adaptability facilitates dynamic data processing, allowing the installation of varying numbers of smart sensors. Additionally, the technology offers customized programming and low-cost, flexible deployments, which can be easily installed by plugging into an electrical outlet in residential and commercial settings.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

  • Program Officer
    Samir M. Iqbalsmiqbal@nsf.gov7032927529
  • Min Amd Letter Date
    8/7/2024 - 4 months ago
  • Max Amd Letter Date
    8/7/2024 - 4 months ago
  • ARRA Amount

Institutions

  • Name
    University of Georgia Research Foundation Inc
  • City
    ATHENS
  • State
    GA
  • Country
    United States
  • Address
    310 E CAMPUS RD RM 409
  • Postal Code
    306021589
  • Phone Number
    7065425939

Investigators

  • First Name
    WenZhan
  • Last Name
    Song
  • Email Address
    wsong@uga.edu
  • Start Date
    8/7/2024 12:00:00 AM
  • First Name
    Jin
  • Last Name
    Ye
  • Email Address
    jin.ye@uga.edu
  • Start Date
    8/7/2024 12:00:00 AM
  • First Name
    Annarita
  • Last Name
    Giani
  • Email Address
    annarita.giani@ge.com
  • Start Date
    8/7/2024 12:00:00 AM

Program Element

  • Text
    PFI-Partnrships for Innovation
  • Code
    166200

Program Reference

  • Text
    POWER, CONTROLS & ADAPTIVE NET
  • Code
    7607